PEK develops analysis of exploration databases using AI, Machine Learning and Analytics in applications that cover a wide range of metals and minerals in order to model and to get a new interpretation of the available data through Data Mining technologies.

In-ground value of the unexplored or existing mineral resources would be estimated across the financial system including to assess about potential quality and asset management.

Assessment to financial institutions and investors through optimizing processes would assure application of capital with AI and machine learning techniques, as well as back-testing models and analyzing the market impact of Greenfield or Brownfield projects.

Hedge funds, broker-dealers and other firms involved with mineral or mining businesses are using it to find signals for higher uncorrelated returns and to optimize deal execution. Both public and private sector institutions may use these technologies for regulatory compliance, surveillance, data quality assessment and fraud detection.

The analysis performed by PEK would reveal a number of potential benefits and risks for financial purposes that should be monitored as the technology is adopted in the analysis and as more data becomes available.

Some applications of AI are:

More efficient processing of information, for example in the valuation of the mineral resources, metal or mineral markets, financial and other industry interactions, may contribute to a more efficient decision making.

The applications of AI and machine learning by regulators and supervisors can help improve regulatory compliance and increase supervisory effectiveness.

Applications of AI and machine learning could result in new and unexpected forms of interconnectedness between the exploration or mining data, financial markets and regulatory institutions.